Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Ghosteken/agent-harness --skill audit-context-buildinggit clone --depth 1 https://github.com/Ghosteken/agent-harnessWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ghosteken/agent-harness/audit-context-building)<a href="https://agentmods.dev/skills/ghosteken/agent-harness/audit-context-building"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/audit-context-building/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ghosteken/agent-harness/audit-context-building"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/audit-context-building.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00027 | $0.02156 |
| Opus 5 | $0.00014 | $0.01078 |
| Sonnet 5 | $0.00005 | $0.00431 |
| Haiku 4.5 | $0.00003 | $0.00216 |
Grade A, and why
audit-context-building scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to audit-context-building — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 309 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Context Builder Skill (Ultra-Granular Pure Context Mode)
1. Purpose
This skill governs how Claude thinks during the context-building phase of an audit.
When active, Claude will:
- Perform line-by-line / block-by-block code analysis by default.
- Apply First Principles, 5 Whys, and 5 Hows at micro scale.
- Continuously link insights → functions → modules → entire system.
- Maintain a stable, explicit mental model that evolves with new evidence.
- Identify invariants, assumptions, flows, and reasoning hazards.
This skill defines a structured analysis format (see Example: Function Micro-Analysis below) and runs before the vulnerability-hunting phase.
When to Use
Use when:
- Deep comprehension is needed before bug or vulnerability discovery.
- You want bottom-up understanding instead of high-level guessing.
- Reducing hallucinations, contradictions, and context loss is critical.
- Preparing for security auditing, architecture review, or threat modeling.
Do not use for:
- Vulnerability findings
- Fix recommendations
- Exploit reasoning
- Severity/impact rating
2. How This Skill Behaves
When active, Claude will:
- Default to ultra-granular analysis of each block and line.
- Apply micro-level First Principles, 5 Whys, and 5 Hows.
- Build and refine a persistent global mental model.
- Update earlier assumptions when contradicted ("Earlier I thought X; now Y.").
- Periodically anchor summaries to maintain stable context.
- Avoid speculation; express uncertainty explicitly when needed.
Goal: deep, accurate understanding, not conclusions.
Rationalizations (Do Not Skip)
| Rationalization | Why It's Wrong | Required Action |
|---|---|---|
| "I get the gist" | Gist-level understanding misses edge cases | Line-by-line analysis required |
| "This function is simple" | Simple functions compose into complex bugs | Apply 5 Whys anyway |
| "I'll remember this invariant" | You won't. Context degrades. | Write it down explicitly |
| "External call is probably fine" | External = adversarial until proven otherwise | Jump into code or model as hostile |
| "I can skip this helper" | Helpers contain assumptions that propagate | Trace the full call chain |
| "This is taking too long" | Rushed context = hallucinated vulnerabilities later | Slow is fast |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 309 lines · 27 tokens per session scan A d37f2823e860
audit-context-building is a skill published in the GitHub repository Ghosteken/agent-harness (2 stars, last pushed today), licensed MIT. It adds 27 tokens to every session and 2,156 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to audit-context-building, differing in 3 lines, and is treated as a copy.
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